Covid Report for Family

Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	New York	20,043
2	New Jersey	18,880
3	Massachusetts	15,400
4	Rhode Island	15,304
5	District of Columbia	13,952
6	Connecticut	12,742
7	Delaware	10,725
8	Illinois	10,686
9	Maryland	10,514
10	Louisiana	10,485
11	Nebraska	8,905
12	Iowa	7,802
13	Mississippi	6,935
14	South Dakota	6,838
15	Michigan	6,678
16	Pennsylvania	6,591
17	Virginia	6,534
18	Indiana	6,244
19	Arizona	5,654
20	Alabama	5,570
21	Minnesota	5,554
22	Georgia	5,388
23	Colorado	5,150
24	Utah	4,823
25	New Mexico	4,800
26	Tennessee	4,702
27	Arkansas	4,508
28	North Carolina	4,494
29	North Dakota	4,159
30	California	4,133
31	Wisconsin	4,058
32	Kansas	4,050
33	New Hampshire	3,997
34	South Carolina	3,992
35	Florida	3,851
36	Nevada	3,847
37	Washington	3,712
38	Ohio	3,629
39	Texas	3,430
40	Kentucky	2,952
41	Missouri	2,794
42	Oklahoma	2,250
43	Maine	2,109
44	Idaho	2,033
45	Wyoming	1,924
46	Puerto Rico	1,879
47	Vermont	1,810
48	Oregon	1,475
49	West Virginia	1,325
50	Alaska	1,060
51	Montana	589
52	Hawaii	516

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	Arizona	238
2	Louisiana	144
3	Mississippi	126
4	Arkansas	122
5	Utah	119
6	Alabama	115
7	Texas	114
8	South Carolina	113
9	Florida	110
10	Tennessee	94
11	North Carolina	93
12	California	87
13	Nebraska	84
14	Rhode Island	83
15	Georgia	73
16	Nevada	70
17	Iowa	69
18	Maryland	68
19	Kansas	63
20	Delaware	61
21	South Dakota	57
22	Indiana	56
23	Oklahoma	56
24	New Mexico	54
25	Virginia	49
26	Washington	49
27	Minnesota	48
28	Oregon	45
29	Illinois	44
30	Wisconsin	44
31	Idaho	41
32	Missouri	41
33	Kentucky	40
34	North Dakota	38
35	District of Columbia	37
36	Ohio	36
37	Colorado	31
38	Connecticut	31
39	New York	31
40	Wyoming	31
41	New Jersey	30
42	New Hampshire	28
43	Pennsylvania	28
44	Massachusetts	26
45	Puerto Rico	20
46	Alaska	19
47	West Virginia	15
48	Michigan	14
49	Maine	10
50	Montana	9
51	Hawaii	3
52	Vermont	1

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New York	1,579
2	New Jersey	1,437
3	Connecticut	1,183
4	Massachusetts	1,121
5	Rhode Island	826
6	District of Columbia	741
7	Louisiana	658
8	Michigan	604
9	Illinois	527
10	Pennsylvania	498
11	Maryland	495
12	Delaware	437
13	Indiana	367
14	Mississippi	315
15	Colorado	283
16	New Hampshire	242
17	Minnesota	240
18	Georgia	238
19	Ohio	223
20	New Mexico	215
21	Iowa	214
22	Virginia	185
23	Arizona	172
24	Alabama	161
25	Washington	161
26	Nevada	153
27	Missouri	150
28	Florida	140
29	California	133
30	Nebraska	123
31	Wisconsin	122
32	Kentucky	119
33	South Carolina	119
34	North Carolina	114
35	North Dakota	102
36	Oklahoma	91
37	South Dakota	88
38	Vermont	88
39	Kansas	85
40	Maine	75
41	Tennessee	72
42	Texas	72
43	Arkansas	65
44	Idaho	49
45	West Virginia	49
46	Puerto Rico	46
47	Utah	46
48	Oregon	43
49	Wyoming	31
50	Montana	18
51	Alaska	13
52	Hawaii	12

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	Rhode Island	13
2	Massachusetts	5
3	Mississippi	5
4	New Jersey	5
5	Illinois	4
6	District of Columbia	3
7	Georgia	3
8	Louisiana	3
9	Maryland	3
10	Nebraska	3
11	Arizona	2
12	Indiana	2
13	Iowa	2
14	New Hampshire	2
15	New Mexico	2
16	New York	2
17	Pennsylvania	2
18	Alabama	1
19	Arkansas	1
20	California	1
21	Colorado	1
22	Connecticut	1
23	Delaware	1
24	Florida	1
25	Minnesota	1
26	Missouri	1
27	North Carolina	1
28	Ohio	1
29	South Carolina	1
30	South Dakota	1
31	Tennessee	1
32	Texas	1
33	Utah	1
34	Virginia	1
35	Alaska	0
36	Hawaii	0
37	Idaho	0
38	Kansas	0
39	Kentucky	0
40	Maine	0
41	Michigan	0
42	Montana	0
43	Nevada	0
44	North Dakota	0
45	Oklahoma	0
46	Oregon	0
47	Puerto Rico	0
48	Vermont	0
49	Washington	0
50	West Virginia	0
51	Wisconsin	0
52	Wyoming	0

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
Trousdale	Tennessee	129,387	1	99
Lake	Tennessee	98,204	2	99
Dakota	Nebraska	87,037	3	99
Buena Vista	Iowa	82,569	4	99
Lincoln	Arkansas	76,397	5	99
Davidson	Tennessee	10,780	228	92
Richland	South Carolina	5,703	570	81
Orange	California	2,896	1126	64
Pierce	Washington	2,738	1183	62
York	South Carolina	2,491	1275	59

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
Hancock	Georgia	3,547	1	99
Randolph	Georgia	3,393	2	99
Terrell	Georgia	3,165	3	99
Early	Georgia	3,042	4	99
Northampton	Virginia	2,306	5	99
Richland	South Carolina	178	652	79
Davidson	Tennessee	131	796	74
Pierce	Washington	98	958	69
Orange	California	77	1079	65
York	South Carolina	39	1456	53

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.